Suppr超能文献

一种用于预测季节性抗生素使用情况下抗生素耐药性频率的进化模型及其应用于…… (原文最后不完整)

An evolutionary model to predict the frequency of antibiotic resistance under seasonal antibiotic use, and an application to .

作者信息

Blanquart François, Lehtinen Sonja, Fraser Christophe

机构信息

Department of Infectious Disease Epidemiology, Imperial College London, London, UK

Department of Infectious Disease Epidemiology, Imperial College London, London, UK.

出版信息

Proc Biol Sci. 2017 May 31;284(1855). doi: 10.1098/rspb.2017.0679.

Abstract

The frequency of resistance to antibiotics in has been stable over recent decades. For example, penicillin non-susceptibility in Europe has fluctuated between 12% and 16% without any major time trend. In spite of long-term stability, resistance fluctuates over short time scales, presumably in part due to seasonal fluctuations in antibiotic prescriptions. Here, we develop a model that describes the evolution of antibiotic resistance under selection by multiple antibiotics prescribed at seasonally changing rates. This model was inspired by, and fitted to, published data on monthly antibiotics prescriptions and frequency of resistance in two communities in Israel over 5 years. Seasonal fluctuations in antibiotic usage translate into small fluctuations of the frequency of resistance around the average value. We describe these dynamics using a perturbation approach that encapsulates all ecological and evolutionary forces into a generic model, whose parameters quantify a force stabilizing the frequency of resistance around the equilibrium and the sensitivity of the population to antibiotic selection. Fitting the model to the data revealed a strong stabilizing force, typically two to five times stronger than direct selection due to antibiotics. The strong stabilizing force explains that resistance fluctuates with usage, as antibiotic selection alone would result in resistance fluctuating behind usage with a lag of three months when antibiotic use is seasonal. While most antibiotics selected for increased resistance, intriguingly, cephalosporins selected for decreased resistance to penicillins and macrolides, an effect consistent in the two communities. One extra monthly prescription of cephalosporins per 1000 children decreased the frequency of penicillin-resistant strains by 1.7%. This model emerges under minimal assumptions, quantifies the forces acting on resistance and explains up to 43% of the temporal variation in resistance.

摘要

近几十年来,抗生素耐药性的频率一直保持稳定。例如,欧洲青霉素不敏感性在12%至16%之间波动,没有任何明显的时间趋势。尽管长期保持稳定,但耐药性在短时间尺度上仍有波动,推测部分原因是抗生素处方的季节性波动。在此,我们开发了一个模型,该模型描述了在按季节性变化速率开具多种抗生素的选择压力下抗生素耐药性的演变。该模型的灵感来源于以色列两个社区5年期间每月抗生素处方和耐药频率的已发表数据,并与之拟合。抗生素使用的季节性波动转化为耐药频率围绕平均值的小波动。我们使用一种微扰方法来描述这些动态,该方法将所有生态和进化力量封装到一个通用模型中,其参数量化了使耐药频率在平衡点附近稳定的力量以及种群对抗生素选择的敏感性。将模型与数据拟合显示出一种强大的稳定力量,通常比抗生素直接选择的力量强两到五倍。这种强大的稳定力量解释了耐药性随使用情况波动的现象,因为仅抗生素选择会导致耐药性在使用情况之后出现三个月的滞后波动,前提是抗生素使用具有季节性。虽然大多数抗生素会导致耐药性增加,但有趣的是,头孢菌素会导致对青霉素和大环内酯类药物的耐药性降低,这一效应在两个社区中是一致的。每1000名儿童每月额外开具一张头孢菌素处方会使青霉素耐药菌株的频率降低1.7%。该模型在最小假设下出现,量化了作用于耐药性的力量,并解释了高达43%的耐药性时间变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e318/5454275/6e3aa4ceea89/rspb20170679-g1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验